Data deduplication often reduces the amount of storage space needed to store backup images by identifying redundant data patterns within similar files. For example, a backup and restore technology may capture a backup image of a client device and identify various data segments that are included in both the backup image and a conventional deduplication system. Rather than storing multiple instances of those data segments to the conventional deduplication system, the backup and restore technology may configure the backup image to simply reference those data segments already stored on the conventional deduplication system. By configuring the backup image to reference those data segments already stored on the conventional deduplication system, the backup and restore technology may reduce the amount of storage space needed to store the backup image on the conventional deduplication system.
Unfortunately, as the number of backup images backed up to the conventional deduplication system increases, the number of data containers used to store the data segments from those backup images may also increase. As a result, the data segments referenced by latter backup images may get scattered throughout various data containers within the conventional deduplication system, thus worsening the locality of those data segments. Furthermore, as the locality of the data segments worsens, the amount of time needed to read and/or restore files that include those data segments from the conventional deduplication system may increase. This process of reading and/or restoring such files is sometimes referred to as “rehydration”. Accordingly, as the number of data containers used by a backup image increases, the rehydration performance of that backup image may decrease.
The instant disclosure, therefore, identifies and addresses a need for additional and improved systems and methods for improving rehydration performance in data deduplication systems.